У відео йдеться про історію винайдення комплексних чисел, які стали вирішенням проблеми від'ємної площі в геометрії і зумовили відмову від геометрії як основи алгебри. Зрештою комплексні числа стали незамінними у фундаментальній фізиці - у рівнянні Шрьодінґера, яке описує хвильову функцію.

✅Текст читав: Андрій Горбунов (канал “Лакуна”)
✅Переклад: Марія Луценко, Марія Ковальчук, Артем Панченко, Катерина Рибачок, Анастасія Євгенова, Анастасія Цьосенко.
✅Редагування, субтитрування, монтаж: Віталій Шевчук (Цікава наука)

❕Підтримайте "Цікаву науку" на https://www.patreon.com/join/CikavaNauka або
💳 Приватбанк: 5168 7451 0521 3422
💳 Монобанк: 4441 1144 2309 4109 (Віталій Шевчук)

© Оригінальне відео: https://www.youtube.com/watch?v=cUzklzVXJwo
© Канал Veritasium: https://www.youtube.com/c/veritasium (з люб’язного дозволу автора)
Executive Producer: Derek Muller
Writers: Derek Muller, Alex Kontorovich, Stephen Welch, Petr Lebedev
Animators: Fabio Albertelli, Jakub Misiek, Iván Tello, Jesús Rascón
SFX: Shaun Clifford
Camerapeople: Derek Muller, Emily Zhang
Editors: Derek Muller, Petr Lebedev
Producers: Derek Muller, Petr Lebedev, Emily Zhang
#SciTube #ЦікаваНаука #WatchUA

A combination of Prompt Engineering and ChatGPT to learn the internals and technology behind large language models powering the new era of Artificial Intelligence.

A List of all prompts and keywords use in this video:
- https://github.com/prodramp/De....epWorks/blob/main/Ch

== Video Timeline ==
(00:00) Content Intro
(01:30) ChatGPT
(02:43) Transformer architecture
(09:10) Keywords Generation
(13:38) Text embedding
(17:43) Encoder and Decoder
(18:32) Self attention
(18:45) Multi-head self attention
(21:56) PyTorch Code Multi-head self attention
(23:37) Scaled Dot Product Attention
(27:45) Key deep learning methods
(28:53) Large language models
(29:49) LLM Parameter Count (Python Code)
(31:38) DALL-E large language model
(33:17) Key Differences DALL-E & ChatGPT
(34:20) List all Prompts
(34:40) ChatGPT Session Summary

Please visit:
https://prodramp.com | @prodramp
https://www.linkedin.com/company/prodramp

Content Creator:
Avkash Chauhan (@avkashchauhan)
https://www.linkedin.com/in/avkashchauhan

Tags:
#llm #chatgpt #promptengineering #openai #python #artificialintelligence

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In this video on "Node JS Full Course 2023," we will learn node js in 6 hours; we will start this entire course from the basics to advanced concepts, equipping you with a solid understanding of this technology. We will start this with an introduction to node js. After that, we will see what a node package manager is. Moving ahead, we will build a REST API with Node js, Node.js Authentication with JWT, and Express js, a framework of node js. We will also create a user registration form using node js and express js.

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05:30:57 - Node js Interview Questions

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With an ever-increasing number of internet users, it’s only convincing that businesses market their products and services using this incredible platform. From small-scale online businesses to big corporations, digital marketing is being rampantly adopted. Learning digital marketing has become the need of the hour and various organizations are constantly on the lookout for skilled executives. So what better than starting a career in digital marketing? Brace yourself to start your career with Simplilearn’s Free Digital Marketing Strategy Training Course.

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Database vs Data Warehouse vs Data Lake | Today we take a look at these 3 different ways to store data and the differences between them.

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Get hands on RAG training in watsonx.ai→ https://ibm.biz/BdK6UZ
Learn about the technology → https://ibm.biz/BdMsRT

Large language models usually give great answers, but because they're limited to the training data used to create the model. Over time they can become incomplete--or worse, generate answers that are just plain wrong. One way of improving the LLM results is called "retrieval-augmented generation" or RAG. In this video, IBM Senior Research Scientist Marina Danilevsky explains the LLM/RAG framework and how this combination delivers two big advantages, namely: the model gets the most up-to-date and trustworthy facts, and you can see where the model got its info, lending more credibility to what it generates.

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MIT 14.02 Principles of Macroeconomics, Spring 2023
Instructor: Ricardo J. Caballero

View the complete course: https://ocw.mit.edu/courses/14....-02-principles-of-ma
YouTube Playlist: https://www.youtube.com/playli....st?list=PLUl4u3cNGP6

This lecture covers an introduction to the topic of macroeconomics, which is the study of the behavior of an economy as a whole. The instructor also talks about the objectives of the course.

License: Creative Commons BY-NC-SA
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Generative AI vs AI Agents vs Agentic AI Explained | Complete Beginner's Guide (2026)

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CREDIT: @ezExplains

Original Video Link: https://youtu.be/DLR0SN2sB4Q?si=8TODgGelnle8wSQi

👉About This Video:
This video has been independently edited, redesigned, and transformed. It contains original commentary, analysis, and educational insights added for the purpose of learning and understanding.
The intention of this content is to educate, inspire, and provide valuable knowledge.



📢 Fair Use Disclaimer:
This video is created under Section 107 of the Copyright Act 1976, which permits fair use for purposes such as criticism, comment, teaching, research, and education.
The content has been transformed, repurposed, and presented with new perspective and value.

Tags:-
#neerajwalia #ai #generativeai #aiagents #agenticai #chatgpt #artificialintelligence #aitutorial #tech #machinelearning #aiexplained